Implement Prometheus Metrics Collection

[Ndevu12]

Overview

Implement Prometheus metrics collection to track key metrics (request count, response time, error rate, cache hit rate) per endpoint.

Why This Matters

• Enables monitoring and alerting
• Provides visibility into system behavior
• Supports performance optimization
• Enables SLA compliance tracking
• Foundation for observability

What Needs to Be Done

1. Install Prometheus client library
2. Configure Prometheus metrics
3. Add request count metrics
4. Add response time metrics
5. Add error rate metrics
6. Add cache hit rate metrics
7. Expose metrics endpoint
8. Add tests for metrics collection

Acceptance Criteria

1. WHEN requests are made, THE Metrics SHALL be collected
2. WHEN metrics are collected, THE Request count SHALL be accurate
3. WHEN metrics are collected, THE Response time SHALL be measured
4. WHEN errors occur, THE Error rate SHALL be tracked
5. WHEN metrics are exposed, THE /metrics endpoint SHALL return Prometheus format

Getting Started

1. Install prometheus-client: pip install prometheus-client
2. Configure metrics in src/api/middleware.py
3. Add metrics collection:
   • Request count per endpoint
   • Response time per endpoint
   • Error rate per endpoint
   • Cache hit rate
4. Expose metrics endpoint:
   • Add /metrics endpoint
   • Return Prometheus format
5. Add tests for metrics collection
6. Document metrics and their meaning

Code References

• Middleware: src/api/middleware.py
• Monitoring: src/monitoring/
• Prometheus Client: https://github.com/prometheus/client_python
• Prometheus: https://prometheus.io/

Definition of Done

• Prometheus client installed
• Metrics configured
• Request count metrics working
• Response time metrics working
• Error rate metrics working
• Cache hit rate metrics working
• /metrics endpoint exposed
• Tests written and passing
• Code review approved
• Documentation updated
• CHANGELOG.md updated

Effort Estimate

2-8 hours

Skill Level

Intermediate

Dependencies

None